ICAT-EGVE2019

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https://diglib.eg.org/handle/10.2312/2632804

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Browsing ICAT-EGVE2019 by Subject "Computing methodologies"

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    Evaluation of Embodied Agent Positioning and Moving Interfaces for an AR Virtual Guide
    (The Eurographics Association, 2019) Techasarntikul, Nattaon; Ratsamee, Photchara; Orlosky, Jason; Mashita, Tomohiro; Uranishi, Yuki; Kiyokawa, Kiyoshi; Takemura, Haruo; Kakehi, Yasuaki and Hiyama, Atsushi
    Augmented Reality (AR) has become a popular technology in museums, and many venues now provide AR applications inside gallery spaces. To improve museum tour experiences, we have developed an embodied agent AR guide system that aims to explain multi-section detailed information hidden in the painting. In this paper, we investigate the effect of different types of guiding interfaces that use this type of embodied agent when explaining large scale artwork. Our interfaces include two types of guiding positions: inside and outside the artwork area, and two types of agent movements: teleporting and flying. To test these interfaces, we conducted a within-subjects experiment to test Inside-Teleport, Inside-Flying, Outside-Teleport, and Outside- Flying with 28 participants. Results indicated that although the Inside-Flying interface often obstructed the painting, most of the participants preferred this type since it was perceived as natural and helped users find corresponding art details more easily.
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    Evaluation of Virtual Reality Tracking Systems Underwater
    (The Eurographics Association, 2019) Costa, Raphael; Guo, Rongkai; Quarles, John; Kakehi, Yasuaki and Hiyama, Atsushi
    The objective of this research is to compare the effectiveness of various virtual reality tracking systems underwater. There have been few works in aquatic virtual reality (VR) - i.e., VR systems that can be used in a real underwater environment. Moreover, the works that have been done have noted limitations on tracking accuracy. Our initial test results suggest that inertial measurement units work well underwater for orientation tracking but a different approach is needed for position tracking. Towards this goal, we have waterproofed and evaluated several consumer tracking systems intended for gaming to determine the most effective approaches. First, we informally tested infrared systems and fiducial marker based systems, which demonstrated significant limitations of optical approaches. Next, we quantitatively compared inertial measurement units (IMU) and a magnetic tracking system both above water (as a baseline) and underwater. By comparing the devices' rotation data, we have discovered that the magnetic tracking system implemented by the Razer Hydra is approximately as accurate underwater as compared to a phone-based IMU. This suggests that magnetic tracking systems should be further explored as a possibility for underwater VR applications.
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    Random-Forest-Based Initializer for Real-time Optimization-based 3D Motion Tracking Problems
    (The Eurographics Association, 2019) Huang, Jiawei; Sugawara, Ryo; Komura, Taku; Kitamura, Yoshifumi; Kakehi, Yasuaki and Hiyama, Atsushi
    Many motion tracking systems require solving inverse problem to compute the tracking result from original sensor measurements, such as images from cameras and signals from receivers. For real-time motion tracking, such typical solutions as the Gauss-Newton method for solving their inverse problems need an initial value to optimize the cost function through iterations. A powerful initializer is crucial to generate a proper initial value for every time instance and, for achieving continuous accurate tracking without errors and rapid tracking recovery even when it is temporally interrupted. An improper initial value easily causes optimization divergence, and cannot always lead to reasonable solutions. Therefore, we propose a new initializer based on random-forest to obtain proper initial values for efficient real-time inverse problem computation. Our method trains a random-forest model with varied massive inputs and corresponding outputs and uses it as an initializer for runtime optimization. As an instance, we apply our initializer to IM3D, which is a real-time magnetic 3D motion tracking system with multiple tiny, identifiable, wireless, occlusion-free passive markers (LC coils). During run-time, a proper initial value is obtained from the initializer based on sensor measurements, and the system computes each position of the actual markers and poses by solving the inverse problem through an optimization process in real-time. We conduct four experiments to evaluate reliability and performance of the initializer. Compared with traditional or naive initializers (i.e., using a static value or random values), our results show that our proposed method provides recovery from tracking loss in a wider range of tracking space, and the entire process (initialization and optimization) can run in real-time.